Evolution of cell cycle control: triangulating the last eukaryotic common ancestor

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Project Summary Cell cycle control is highly conserved through the eukaryotic kingdom, and the budding yeast model system has been the source of major insights applicable to issues in human development and disease. This proposal continues systems-level analysis of the eukaryotic cell cycle using this model system. The cell cycle `clock' functions with high reliability and low noise, even though individual components and circuits making up the clock are frequently known to be highly variable. For example, gene expression is known to be highly variable between individual cells, and yet cell-cycle-regulated gene expression can be highly reliable with respect to timing and amplitude. Threshold responses to rising cyclin-Cdk activity levels can provide switch-like behavior, but such switches can frequently come at the cost of highly variable onset time; the overall cell cycle control circuitry avoids this variability. We are pursuing an emerging concept of multiple independent oscillators contributing to cell cycle control; while uncoupled oscillators result in highly variable and irregular sequences of cell cycle events, we propose that coupling (`phase-locking') of otherwise independent oscillators to the central cyclin-Cdk oscillator can yield a robust and accurate overall system. This proposal continues our innovative use of quantitative time-lapse fluorescence microscopy, over multi-cell cycle timescales, combined with semi-automated image analysis and in-depth genetic and quantitative analysis to drive systems-level understanding of cell cycle control. We are developing new methods of mathematical modeling. There is a pressing need in biology for simple but experimentally constrained models that can reveal basic control principles. The challenge is to find the most illuminating balance between the detail required for a connection to biological reality, and model simplicity required for transparency and insight. We are exploring methods to use geometrical, low-dimensionality representations of the cell cycle control network that can still be experimentally constrained, and that will yield testable predictions.